Monitoring apparatus and monitoring object apparatus

ABSTRACT

A monitoring system for monitoring the state of a monitoring object apparatus so as to detect a foretoken of failure. A host computer ( 100 ) of a manufacturer/dealer of a clinical check apparatus ( 200 ) receives state data of respective parts from parts sensors ( 203   a   , 203   b, . . . ) of the clinical check apparatus ( 200 ) of a user and the received state data is compared to a prediction condition stored in a condition storage block ( 104 ) in a state monitoring block ( 105 ), thereby detecting a foretoken of failure. The prediction condition includes a condition created in accordance with service life of each of the parts and a condition created upon occurrence of a failure in accordance with transition of the state data prior to the occurrence of the failure.

TECHNICAL FIELD

The present invention relates to a system in which a monitoring deviceremotely monitors various devices to be monitored through acommunication network so as to predict a failure or the like of each ofthe monitored devices.

BACKGROUND ART

Generally, with respect to various testing devices including clinicaltesting devices, machine tools or automobiles, or various types of otherdevices requiring precise operations, manufacturers/dealers of suchdevices, after delivery of the devices, continuously perform maintenanceso that performance of the devices is maintained and safety is secured.Particularly, the occurrence of a failure in a device may hinder anoperator of the device from performing a smooth operation or also maycause safety hazards to the operator. Therefore, with a view toimproving customer satisfaction, suppressing an increase in maintenancecost and securing safety, it has been of great importance to perform aperiodic check of a device and advance replacement of a consumablecomponent and the like so as to prevent a failure from being caused.

Conventionally, it is generally the case that times at which a periodiccheck and replacement of a component are to be performed are setsuitably by a human being based on a past experience rule.Alternatively, there also are cases where such times are set based onlife data for each component.

However, in the case where the time for a check/replacement is set basedsimply on a past experience rule or life data for each component or thelike as described above, since there are life variations even amongcomponents of the same type due to the differences in usage conditionsand the like, the following problem may arise. That is, contrary toexpectations, a failure may be caused before the time for acheck/replacement, or conversely, a component that still has sufficientlife may have to be replaced, thereby resulting adversely in an increasein the maintenance cost, which has been disadvantageous.

DISCLOSURE OF THE INVENTION

With the foregoing in mind, it is an object of the present invention toprovide a monitoring system that allows a maintenance check to beperformed at an appropriate time with respect to a monitored device bymonitoring the state of the device through a communication network so asto detect an indication of an abnormality, thereby allowing the deviceto achieve a higher normal operating ratio and the suppression of anincrease in maintenance cost.

In order to achieve the above-mentioned object, a monitoring deviceaccording to the present invention includes a status data receiving partthat receives status data representing a status of a monitored devicefrom the monitored device through a communication network, a conditionstoring part that stores a condition for prediction, and a statusmonitoring part that compares the status data with the condition forprediction in the condition storing part so as to predict anabnormality. In the device, the condition for prediction includes acondition for prediction created based on a transition of the statusdata before a point in time at which the abnormality is caused in themonitored device.

In this configuration, with respect to the status data received from themonitored device, upon sequential reception thereof, a comparison ismade with the condition for prediction stored in the condition storingpart so that an abnormality of the monitored device is predicted. As acondition constituting the condition for prediction, a condition may beused that is created based on a transition of the status data before apoint in time at which the abnormality is caused, and thus theoccurrence of the abnormality can be predicted more accurately. Thus, amonitoring device can be realized that allows a monitored device toachieve: a higher normal operating ratio compared with a conventionalcase where a time for a maintenance check is set suitably based on lifedata of a component or the like; and the suppression of an increase inmaintenance cost to be incurred in the case where a maintenance serviceis performed by a manufacturer/dealer or the like of the monitoreddevice.

Preferably, in the monitoring device, the condition for prediction thuscreated is a condition created based on transitions of the status datawith a common change pattern among transitions of the status data thatare observed in at least two monitored devices in which a commonabnormality is caused.

For example, in the case where an accidental abnormality is caused, achange pattern of the status data obtained right before the occurrenceof the abnormality may not necessarily provide a reliable indication ofthe abnormality. The use of a condition for prediction created based onsuch a change pattern even may result adversely in decreased accuracy inpredicting an abnormality. Therefore, as in the above-mentionedconfiguration, a condition for prediction is created based on a commonchange pattern obtained in the case where a common abnormality iscaused, and thus a general condition for prediction used to detect anindication of an abnormality can be set. This allows an abnormality tobe predicted more accurately.

Preferably, the monitoring device further includes a data storing partthat accumulates the status data received from the monitored device, andan abnormality analyzing part that creates the condition for predictionbased on the transition of the status data before the point in time atwhich the abnormality is caused using the status data accumulated in thedata storing part and has the condition for prediction stored in thecondition storing part.

According to this configuration, the abnormality analyzing part createsa condition for prediction based on status data received from amonitored device in actual operation by a user and has the condition forprediction stored in the condition storing part. Thus, a condition forprediction can be created objectively, and it also is possible to savehuman time and effort to create a condition for prediction.

Preferably, in the monitoring device, the condition for predictionfurther includes a condition for prediction created based on life dataof a component of the monitored device.

According to this configuration, a condition for prediction createdbased on a transition of status data when an abnormality actually iscaused and a condition for prediction created based on life data of acomponent are used in combination. Thus, an abnormality that can becaused due to the wearing out of a component can be predicted moreaccurately, thereby allowing a maintenance check of a monitored deviceto be performed at a more appropriate time.

Preferably, in the monitoring device, the status data includes outputsof various types of sensors that are provided in the monitored device,and the condition for prediction includes a condition for predictioncorresponding respectively to the outputs of the various types ofsensors.

According to this configuration, monitoring is performed based onvarious types of status data, and thus a status of a monitored devicecan be judged more properly, thereby allowing an abnormality to bepredicted even more accurately.

Preferably, the monitoring device includes a communication part thattransmits a notification that an abnormality is predicted by the statusmonitoring part to the monitored device through the communicationnetwork. Furthermore, more preferably, the communication part transmitsa direction on how to correct the abnormality.

These configurations allow a user of a monitored device to take properactions.

In the case where the monitored device includes a light source, and alight amount of the light source is output as the status data, in themonitoring device, a condition for prediction used to predict anabnormality of the light source may be that the tendency of the statusdata corresponding to the light amount of the light source is turnedtoward an increase in value, or that a change rate of a value of thestatus data corresponding to the light amount of the light sourcedeviates from a predetermined range.

That is, a light amount of a light source may increase temporarily orbecome unstable before an abnormality such as breaking of a lamp or thelike is caused in the light source. Thus, the above-mentioned conditionfor prediction is used, thereby allowing an abnormality of a lightsource in a monitored device to be detected more accurately.

Furthermore, in the case where the monitored device includes a componentthat is driven by a pulse motor, and the number of pulses of the pulsemotor driving the component is output as the status data, in themonitoring device, a condition for prediction used to predict anabnormality of the component may be that a value of the status datacorresponding to the number of pulses of the pulse motor deviates from apredetermined range of the number of pulses.

For example, in the case where the friction resistance or the like of acomponent driven by a pulse motor is increased for some reason, a lossof synchronization may be caused in the pulse motor, resulting inrequiring a larger number of pulses for the component to perform apredetermined operation than in a normal case. Thus, the above-mentionedcondition for prediction is used, thereby allowing an abnormality ofsuch a component in a monitored device to be detected more accurately.

Preferably, in the monitoring device, the monitored device includes acomponent that performs a predetermined operation repeatedly in the casewhere the predetermined operation has failed to be completedsuccessfully, the number of repetitions of the predetermined operationperformed till successful completion is output as the status data, and acondition for prediction used to predict an abnormality of the componentincludes that a value of the status data corresponding to the number ofrepetitions becomes higher than values in a predetermined range. Thisallows an abnormality of such a component in a monitored device to bedetected more accurately. In order to achieve the above-mentionedobject, a monitored device according to the present invention is amonitored device that is monitored by any of the above-mentionedmonitoring devices and includes a sensor part that outputs the statusdata and a communication part that transmits the status data to themonitoring device through a communication network.

According to this configuration, status data is transmitted to amonitoring device through a communication network, and thus it is madepossible to receive an abnormality predicting service by remotemonitoring. This allows a monitored device to be provided that has ahigh normal operating ratio and can be reduced in maintenance cost.

Preferably, in the monitored device, the communication part transmitsthe status data immediately after the status data is output from thesensor part. This provides an advantage of allowing a status of amonitored device to be kept always up to date in a monitoring device.

Preferably, in the monitored device, a memory part that accumulates thestatus data output from the sensor part is provided, and thecommunication part transmits the status data accumulated in the memorypart at a predetermined timing. This provides an advantage of allowingthe transmission efficiency of data to be improved.

In order to achieve the above-mentioned object, a first programaccording to the present invention is a program that allows a computerto perform a process characterized by: receiving status datarepresenting a status of a monitored device from the monitored device;comparing a condition for prediction including a condition created basedon a transition of the status data before a point in time at which anabnormality is caused in the monitored device with the status data; andproviding to the monitored device a notification that the abnormality ispredicted when the status data meets the condition for prediction.

This program is read into a computer so as to be performed, therebyallowing the monitoring device according to the present invention to berealized.

In order to achieve the above-mentioned object, a second programaccording to the present invention is a program that allows a computerto perform a process characterized by: accumulating status data receivedfrom a monitored device in a data storing part; and creating a conditionfor prediction of an abnormality based on a transition of the statusdata before a point in time at which the abnormality is caused using thestatus data accumulated in the data storing part.

This program is read into a computer so as to be performed, therebyallowing the monitoring device according to the present invention to berealized that automatically creates a condition for prediction based onstatus data obtained from a monitored device in operation.

In order to achieve the above-mentioned object, a third programaccording to the present invention is a program that is read into acomputer mounted in a monitored device monitored by any of theabove-mentioned monitoring devices. The third program allows thecomputer to perform a process characterized by transmitting an output ofa sensor part as status data to the monitoring device through acommunication network.

This program is read into a computer mounted in a monitored device so asto be performed, thereby allowing the monitored device according to thepresent invention to be realized.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram schematically showing a configuration of amonitoring system according to an embodiment of the present invention.

FIG. 2 is a graph showing an example of a change pattern of status dataof a clinical testing device monitored in the monitoring system, whichis used as a basis on which a condition for prediction is created.

FIG. 3 a graph showing another example of the change pattern of thestatus data of the clinical testing device, which is used as the basison which the condition for prediction is created.

FIG. 4 is a perspective view showing a configuration of a test stripfeeder provided in a device as an example of the clinical testingdevice.

FIG. 5 is an enlarged perspective view showing a rotor and the peripherythereof shown in FIG. 4.

FIG. 6 is a cross sectional view taken on line X—X of FIG. 4.

FIG. 7 is a graph showing a change pattern of a set of status dataobtained with 100 measurements performed during a time preceding a pointin time at which test strip jamming is caused.

FIG. 8 is a graph showing a change pattern of a set of status dataobtained with 100 measurements performed during a time further precedingthe 100 measurements shown in FIG. 7.

BEST MODE FOR CARRYING OUT THE INVENTION

(Embodiment 1)

Hereinafter, the present invention will be described by way of anembodiment with reference to the appended drawings.

As shown in FIG. 1, a monitoring system according to this embodiment hasa configuration in which a host computer 100 (monitoring device) of amanufacturer/dealer of a device such as a clinical testing device or thelike and a clinical testing device 200 (monitored device) that has beendelivered to a user by this manufacturer/dealer are connected to eachother through a communication network 300 such as the Internet. In FIG.1, for the sake of simplicity, only one unit of the clinical testingdevice 200 is shown. However, an arbitrary number of units of theclinical testing devices 200 are connected to the host computer 100.

The communication network 300 is not limited to the Internet mentionedabove and can be formed of any communication medium that is capable ofbi-directional communication. Through this communication network 300,data representing a status of the device (hereinafter, referred to asstatus data), an error signal, a trouble signal and the like aretransmitted from the clinical testing device 200 to the host computer100. Further, a data requesting signal, contents of a manual foroperating the clinical testing device 200 and the like are transmittedfrom the host computer 100 to the clinical testing device 200.

In this embodiment, an “error” refers to an operational abnormalityattributable mainly to an operational error by a user or the like anddoes not require repair or the like to be made on the device itself. Forexample, an “error” is a phenomenon in which a measurement is terminatedbecause no test paper to be used for the measurement has been set. Thiscase does not require repair or the like because an operation returns tonormal once the test paper is set by the user. On the other hand,“trouble” refers to an operational abnormality attributable to anabnormality caused in the device and is a phenomenon that requiresrepair, replacement of a component and the like. The host computer 100as the monitoring device is to predict the trouble.

As shown in FIG. 1, the host computer 100 includes a communication part101, a controlling part 102, a data storing part 103, a conditionstoring part 104, a status monitoring part 105, and an abnormalityanalyzing part 106.

The communication part 101 transmits such data and the like as describedabove to and receives the same from the clinical testing device 200through the communication network 300. The controlling part 102 controlsoperations of the respective parts of the host computer 100 according toa predetermined program. The data storing part 103 stores status datatransmitted from the clinical testing device 200. The condition storingpart 104 stores a condition (referred to as a condition for prediction)that appears in the status data and indicates an abnormality. The statusmonitoring part 105 monitors the status data in comparison with thecondition for prediction so as to judge whether or not a maintenanceoperation or the like needs to be performed with respect to the clinicaltesting device 200. In the case of trouble, the abnormality analyzingpart 106 analyzes a change in the status data that has been caused as anindication of the trouble using the status data obtained right before apoint in time at which the trouble is caused.

As shown in FIG. 1, the clinical testing device 200 includes acommunication part 201, a controlling part 202, component sensors 203a–203 b and the like, and a displaying part 204. In FIG. 1, for the sakeof simplification, with respect to the clinical testing device 200, onlya block of a control system relevant to the prediction of an abnormalityis shown. However, for example, any functional block for achieving theintended purpose of the clinical testing device 200 can be provided.

The communication part 201 transmits such data and the like as describedabove to and receives the same from the host computer 100 through thecommunication network 300. The controlling part 202 controls operationsof the respective parts of the clinical testing device 200 according toa predetermined program. The component sensors 203 a–203 b and the likeare sensors that are attached respectively to at least components withthe possibility of leading to an operational abnormality amongconstituent components of the clinical testing device 200. The componentsensors 203 a–203 b and the like produce outputs in the form of statusdata representing a status of each of the at least components. Thedisplaying part 204 displays on a screen, in addition to a message to auser as a prompt and contents of an operation manual transmitted fromthe host computer 100, a message notifying a user of an error, troubleand the like.

The following description is directed to an operation of this monitoringsystem in the case where a urine analyzing device is used as theclinical testing device 200.

The urine analyzing device as the clinical testing device 200 sucks asample (urine) using a nozzle from a spitz tube set in a sample rack andapplies the same to a reagent pad of test paper by spotting. Then, thedevice irradiates light having a predetermined wavelength onto this testpaper so as to measure a reflectance of the light, thereby performing adetermination for urine sugar, urine protein and the like. Further, thedevice also has a function of measuring a specific gravity based on arefractive index of light irradiated onto a sample in a sample rack anda function of measuring turbidity using scattered light. The devicefurther includes a conveying part that moves a sample rack in ahorizontal direction so that an automatic conveying line can beestablished between the device and another device, between which acommon sample rack is shared, and a plurality of sample racks can beused sequentially.

Thus, as the component sensors 203, the urine analyzing device includesvarious types of sensors in the respective parts, which are, forexample, (1) a sensor that counts the number of times of use of asyringe pump for allowing the nozzle to perform a sucking operation andoutputs the number thus obtained, (2) a sensor that determines anoperation time of an air pump (diaphragm pump) and outputs the time thusobtained, (3) a sensor that measures a pressure in a drainage passageand outputs a value of the pressure thus obtained, (4) a sensor thatmeasures a light amount of a light source lamp for measurement andoutputs the light amount thus obtained, and (5) a sensor that measures africtional resistance of the sample rack conveying part and outputs thefriction resistance thus obtained and the like.

The timing at which these pieces of data are output respectively fromthe sensors should be set arbitrarily according to the respectiveproperties of the components. Further, one component may be providedwith two or more types of the component sensors 203 so that two or moretypes of status data can be detected. For example, in theabove-mentioned syringe pump, in addition to the sensor that counts thenumber of times of use, a sensor further may be provided as thecomponent sensor 203, which detects, with respect to a pulse motordriving a syringe to move vertically, the numbers of driving pulsesobtained respectively when the syringe moves upwardly and when thesyringe moves downwardly.

The pieces of data (status data) output respectively from theabove-mentioned component sensors 203 are transmitted as required fromthe communication part 201 to the host computer 100 through thecommunication network 300 under the control of the controlling part 202.Then, the pieces of data are stored in the data storing part 103.

The status data may be transmitted from the clinical testing device 200to the host computer 100 each time the status data is output from eachof the component sensors 203. Alternatively, a memory (not shown) thattemporarily stores the status data may be provided in the clinicaltesting device 200 so that upon accumulation of a certain amount of thestatus data, the accumulated set of status data may be transmitted. Theformer method has an advantage of allowing a status of the clinicaltesting device 200 to be kept always up to date in the host computer100. The latter method has an advantage of allowing the transmissionefficiency of data to be improved.

In the host computer 100, the status monitoring part 105 compares thestatus data stored in the data storing part 103 with the condition forprediction stored in the condition storing part 104 so as to judge astatus of the clinical testing device 200.

As an initial value of a condition for prediction, a condition based onlife data of each component or the like is set in the condition storingpart 104. For example, with respect to the status data from the syringepump that is obtained as described above in Item (1), it is set as aninitial value of the condition for prediction that “the number of timesof use reaches 10,000”. Further, with respect to the status data fromthe air pump that is obtained as described in Item (2), for example, itis set as such an initial value that “the operation time reaches 5,000hours”. With respect to the status data from the drainage passage thatis obtained as described in Item (3), for example, it is set as such aninitial value that “a decrease in pressure in the passage is less than60 kPa after an elapse of 5 seconds from the start of pump driving”.With respect to the status data from the light source lamp formeasurement that is obtained as described in Item (4) , it is set assuch an initial value that “a light amount of the lamp becomes not morethan 70% of an initial value”. With respect to the status data from thesample rack conveying part that is obtained as described in Item (5) ,it is set as such an initial value that “a friction becomes not lessthan a certain value (N)”.

Furthermore, in the condition storing part 104, a situation handlingmethod also is stored in relation to each of these conditions forprevention. For example, regarding the case where the above-mentionedcondition for prediction for the syringe pump with respect to Item (1)is met, “greasing the syringe” and “replacing an O-ring” are stored asthe situation handling methods. Further, regarding the case where thecondition for prediction for the air pump with respect to Item (2) ismet, “replacing the pump” is stored as such a situation handling method.Regarding the case where the condition for prediction for the drainagepassage with respect to Item (3) is met, “clearing clogging inside thepassage, or confirming a deterioration in the ability of the pump so asto replace the pump if necessary” is stored as such a situation handlingmethod. Regarding the case where the condition for prediction for thelight source lamp with respect to Item (4) is met, “replacing the lamp”is stored as such a situation handling method. Regarding the case wherethe condition for prediction for the sample rack conveying part withrespect to Item (5) is met, “cleaning a portion in which friction iscaused” is stored as such a situation handling method.

The status monitoring part 105 compares the status data from theclinical testing device 200 with the condition for prediction. If thestatus data meets the condition for prediction, the status monitoringpart 105 transmits to the clinical testing device 200 through thecommunication part 101 and the communication network 300, for example, amessage for giving a direction on the situation handling method storedin relation to the condition for prediction in the condition storingpart 104 along with a message for making an alarm indicating anextremely high possibility of the occurrence of an abnormality. In theclinical testing device 200, upon the reception of these messages andthe like by the communication part 201, the displaying part 204 displaysthe situation handling method on a screen under the control of thecontrolling part 202. Thus, a user of the clinical testing device 200 isallowed to, for example, perform self-handling of the situationaccording to the message displayed on the screen or the like.Alternatively, in the case where the self-handling does not work, theuser is allowed to, for example, request dispatching of maintenancepersonnel.

However, in practice, under the influence of, for example, a state ofuse, a maintenance status, or variations in conditions under which acomponent is manufactured, in some cases, an abnormality is causedbefore the status data meets the condition for prediction set initially.Conversely, in other cases, an abnormality is not caused even after apoint in time at which the status data meets the condition forprediction.

With this in view, as will be described hereinafter, when an abnormalityactually is caused, the host computer 100 according to this embodimentrefers to the status data stored in the data storing part 103. Then, thehost computer 100 creates a new condition for prediction based on achange pattern of the status data obtained right before a point in timeat which the abnormality is caused and adds the same in the conditionstoring part 104. After this, the status monitoring part 105 comparesthe condition for prediction set initially as well as the condition forprediction thus added with the status data so as to monitor the clinicaltesting device 200. If the status data meets any of the conditions forprediction, the status monitoring part 105 transmits the above-mentionedmessages or the like, i.e., for example, the message for creating analarm and the message for giving a direction on the situation handlingto the clinical testing device 200.

The following description is directed to a method of setting a newcondition for prediction when an abnormality is caused. The method isset based on a change pattern of status data obtained right before theabnormality is caused. The description specifically illustrates anexample in which in the above-mentioned urine analyzing device, andbreaking is caused in the light source lamp for measurement.

FIG. 2 is a graph showing a transition of status data from the lightsource lamp for measurement, namely, a light amount of the lamp that ismeasured by any of the component sensors 203 and transmitted to the hostcomputer 100. As shown in the figure, after an elapse of about 6,000hours from the start of lamp use, breaking was caused in the lamp.

When breaking is caused in the light source lamp, the component sensor203 for the lamp detects the occurrence of trouble, i.e. “breaking inthe light source lamp” and outputs a trouble signal allotted beforehandto this type of trouble. This trouble signal is transmitted to the hostcomputer 100 through the communication part 201 and the communicationnetwork 300.

In the host computer 100, upon the reception of this trouble signal bythe communication part 101, under the control of the controlling part102, the abnormality analyzing part 106 extracts from the data storingpart 103 status data obtained during a predetermined period preceding apoint in time at which this trouble signal is received. Then, theabnormality analyzing part 106 analyzes the status data thus extracted,extracts a change pattern as an indication of an abnormality, and sets anew condition for prediction.

For example, in the status data shown in FIG. 2, the light amount of thelamp as the status data is decreased gradually after the start of lampuse. However, as can be seen from the figure, the light amount exhibitsa tendency that turns toward an increase before the breaking is causedin the lamp. Therefore, as a new condition for prediction, it is addedin the condition storing part 104 that “the light amount of the lamp isincreased”. Thus, after this, with respect to the light amount of thelamp as the status data of the light source lamp, when either of thecondition that “the light amount of the lamp becomes not more than 70%of the initial value” and the condition that “the light amount of thelamp is increased” is met, a message for making an alarm or the like isissued.

Furthermore, for example, in the case where the light amount of the lamphas a change pattern as shown in FIG. 3, as can be seen from the figure,the light amount is unstable before the breaking is caused in the lamp.Therefore, in this case, for example, it may be newly added as acondition for prediction in the condition storing part 104 that “thechange rate of the light amount of the lamp deviates from apredetermined range”.

Furthermore, with respect to the above-mentioned syringe pump, forexample, in the case where an abnormality was caused in vertical drivingof the syringe before the condition for prediction set initially wasmet, namely before the number of times of use reached 10,000, ananalysis was made, with respect to the pulse motor driving the syringeto move vertically, on the numbers of driving pulses obtainedrespectively when the syringe moved upwardly and when the syringe moveddownwardly. As a result, it was revealed that a deviation of 4 pulses ormore was generated right before a point in time at which the abnormalitywas caused. In this case, it should be added as a new condition forprediction in the condition storing part 104 that “the differencebetween the numbers of driving pulses obtained respectively when thesyringe of the pulse motor moves upwardly and when the syringe movesdownwardly becomes 4 or more”.

As described above, according to the configuration of this embodiment, acondition for prediction based on life of a component or the like is setinitially in the condition storing part 104. In the case of the actualoccurrence of an abnormality, a new condition for prediction is added inthe condition storing part 104, which is created based on a changepattern of status data obtained right before a point in time at whichthe abnormality is caused. This allows the status monitoring part 105 todetect an indication of an abnormality more accurately.

A new condition for prediction based on a change pattern of status datamay be created by the abnormality analyzing part 106 according to apredetermined algorithm or may be created and set by a human being basedon a change pattern extracted and analyzed by the abnormality analyzingpart 106.

(Embodiment 2)

Hereinafter, the present invention will be described by way of anotherembodiment.

In this embodiment, as an example of the clinical testing device 200, adevice is used that is provided with a test strip feeder part (not shownin FIG. 1) supplying a testing part with test strips. The description isdirected to a mechanism in which an operational abnormality of thisdevice is predicted by the host computer 100.

As shown in FIG. 4, a test strip feeder included in the clinical testingdevice 200 is a mechanism for sequentially supplying a predeterminedtesting part with test strips one at a time. A test strip is a thin andshort strip having one side with a surface on which many different typesof reagent pads are disposed.

As shown in FIG. 4, the test strip feeder includes a base 1, supports 2,supporting members 3 a and 3 b, a rotor 4, a lodging portion 5, a teststrip detecting block 6, an inclined cover 7, a drum 8, a base member 9,a driving portion 10, and a drum controlling portion (not shown). Thedrum controlling portion is formed of a microcomputer or the like.

The supporting members 3 a and 3 b, the lodging portion 5 and the teststrip detecting block 6 form peripheral side walls of a supplyingportion 11 in which a plurality of test strips are supplied. The rotor 4takes out a test strip one at a time from the supplying portion 11 so asto feed it to the drum 8. A photo sensor 6 a (see FIG. 6) isincorporated within the test strip detecting block 6. This sensordetects the sides of one test strip fed from the rotor 4 to the drum 8.

A pulse motor 10A for supplying the rotational power to the rotor 4 andthe drum 8 is incorporated in the driving portion 10. A driving shaft ofthe pulse motor 10A is coupled to rotary shafts of the rotor 4 and thedrum 8 through a driving transmitting system 10B including a belt,pulleys 10Ba and 10Bb and the like, a part of which is not shown in thefigure.

In this test strip feeder, as the component sensors 203 shown in FIG. 1,various types of sensors including the photo sensor 6 a are provided totransmit status data of each component to the host computer 100.

FIG. 5 is an enlarged perspective view showing the rotor 4 and theperiphery thereof shown in FIG. 4. FIG. 6 is a cross sectional viewtaken on line X—X of FIG. 4. As shown in FIGS. 4 to 6, the rotor 4 isformed so as to have an external column-like shape that is longer thanwide as a whole and constituted schematically of an outer peripheralportion 4 a, a rotary shaft 4 b and spoke members 4 c. The outerperipheral portion 4 a is formed so as to have a cylindrical shape thatis longer than wide and a dimension in a longitudinal direction thatcorresponds substantially to a longitudinal length of a test strip.While being positioned at a center inside the outer peripheral portion 4a, the rotary shaft 4 b is coupled to an inner side face 4 aa of theouter peripheral portion 4 a through the spoke members 4 c. Each endportion of this rotary shaft 4 b is inserted into a through holeprovided at a predetermined portion of each of the supporting members 3a and 3 b. The rotor 4 is set so as to be rotatable while beingsupported by the shaft between the supporting members 3 a and 3 b.

Meanwhile, concave portions 4 d in the form of a plurality of lines ofdeep grooves are formed on an outer side face 4 ab of the outerperipheral portion 4 a so as to make a round along a rotationaldirection. Further, a groove portion 4 e that is longer than wide isformed on the outer side face 4 ab so that one test strip can be fit inthe groove portion 4 e along a longitudinal direction orthogonal to therotational direction.

Under the control of the driving portion 10, the rotor 4 performs areciprocating rotational motion between a position (initial position) atwhich the groove portion 4 e is positioned below the lodging portion 5and a position (judging position) that allows the photo sensor 6 a tojudge whether or not a test strip is present in the groove portion 4 e.A rotation angle is controlled based on the number of driving pulses ofthe pulse motor 10A, and a rotational position of the rotor 4 isdetected by the photo sensor 6 a. That is, when the pulse motor 10A isdriven by a predetermined number of pulses (for example, 500 pulses) soas to rotate the rotor 4 from the initial position, if it is detected bythe photo sensor 6 a that the rotor 4 is in the judging position, it isjudged that the rotor 4 operates normally.

When a plurality of test strips are supplied by a user in the supplyingportion 11 while being aligned in a longitudinal direction, as shown inFIG. 3, the rotor 4 starts to rotate in a counterclockwise directionfrom the initial position. At this time, one of the test strips that ispositioned at the bottom of the supplying portion 11, while being fit inthe groove portion 4 e of the rotor 4, is moved in a direction of thetest strip detecting block 6 as the rotor 4 rotates. In this case, theplurality of test strips supplied in the supplying portion 11 are piledup on the outer side face 4 ab of the rotor 4 including the grooveportion 4 e. When the groove portion 4 e is moved to a position wherethe groove portion 4 e faces the test strip detecting block 6, the teststrips piled up in the groove portion 4 e are sorted into only one stripby a partitioning plate 6 e.

The rotor 4 rotates further, and thus the one test strip fit in thegroove portion 4 e, while being integrated with the groove portion 4 e,is passed through the test strip detecting block 6 and reaches thejudging position. At this position, the photo sensor 6 a of the teststrip detecting block 6 detects whether or not a test strip is fit inthe groove portion 4 e. In the case where the photo sensor 6 a detects atest strip, namely, when it is confirmed that the rotor 4 has rotated tothe judging position, the driving portion 10 drives the pulse motor 10Afurther by a predetermined number of pulses so that the rotor 4 isrotated further in the counterclockwise direction. Thus, the test stripis ejected to an inclined passage 12.

If it is not detected by the photo sensor 6 a that the rotor 4 hasrotated to the judging position even when the rotor 4 has been rotatedby 500 pulses, conceivably, the reason is that the test strip is stuckbetween the rotor 4 and the partitioning plate 6 e, and thus the rotor 4is hindered from rotating.

In this case, in order to remove the stuck test strip, as describedabove, the driving portion 10 once drives the rotor 4 back to theinitial position and restarts a rotational operation. The componentsensor 203 provided in the driving portion 10 outputs to the hostcomputer 100, as status data, the number of times (number of trials)this operation is performed until one test strip is ejected to theinclined passage 12. In the case where it is not detected that the rotor4 has rotated to the judging position even when this operation isrepeated a predetermined number of times (for example, 50 times), atrouble signal representing the occurrence of “test paper jamming” isoutput from the component sensor 203 of the driving portion 10 andtransmitted to the host computer 100 through the communication part 201and the communication network 300.

In the host computer 100, upon the reception of this trouble signal bythe communication part 101, under the control of the controlling part102, the abnormality analyzing part 106 extracts from the data storingpart 103 status data obtained during a suitable period preceding a pointin time at which this trouble signal is received.

Herein, it is assumed that the abnormality analyzing part 106 extractedas status data obtained right before a point in time at which anabnormality was caused, for example, status data obtained in 100 timesof measurements performed during a time preceding a point in time atwhich “test strip jamming” was caused (namely, the number of trials thathad been performed so as to take out 100 test strips). A change patternof the status data is shown in FIG. 7. Further, the abnormalityanalyzing part 106 extracts from the data storing part 103, status dataobtained with 100 measurements performed during a time further precedingthe 100 measurements as data at a normal status for comparison with thestatus data obtained right before the abnormality was caused. A changepattern of this data at the normal status is shown in FIG. 8.

As can be seen by the comparison between FIG. 7 and FIG. 8, in a normalstatus (FIG. 8), the number of trials performed until one test strip isremoved is 3 to 4 on the average, while right before a point in time atwhich an abnormality was caused (FIG. 7), the number of trials isincreased abruptly to 6 to 10 on the average. Therefore, for example, itis added as a new condition for prediction to the condition storing part104 that “the average of the number of trials becomes 9 or higher”.Thus, after this, the status monitoring part 105 monitors the number oftrials as status data based on this condition for prediction, therebyallowing an indication of the occurrence of test strip jamming to bedetected.

Furthermore, in the driving part 10, another type of the componentsensor 203 also is provided that outputs to the host computer 100, asstatus data, the number of feed pulses of the pulse motor 10A requiredto rotate the rotor 4 from the initial position to the judging position.The status data obtained by this component sensor 203 was analyzed bythe abnormality analyzing part 106. As a result, it was found that in anormal case, the number of feed pulses required for the rotation fromthe initial position to the judging position was 500 pulses as describedabove, while right before a point in time at which the test stripjamming was caused, the number was not less than 560 pulses.

Therefore, it is added further as a new condition for prediction to thecondition storing part 104 that “the number of feed pulses of the pulsemotor becomes not less than 550 pulses”, thereby allowing an indicationof the occurrence of test strip jamming to be detected more accurately.

Right before the occurrence of test strip jamming, the number of trialsperformed is increased or the number of feed pulses of a pulse motor isincreased because of the following reason. That is, dust generated froma test strip is stuck to a surface of the rotor 4, the groove portion 4e or the like, so that it becomes more likely that a test strip is stuckbetween the rotor 4 and the partitioning plate 6 e and the rotationalfriction resistance of the rotor 4 is increased. Thus, preferably, inthe case where an indication of the occurrence of test strip jamming isdetected, a message for giving a direction to “clean the rotor and thegroove portion” is transmitted as a situation handling method from thehost computer 100 to the clinical testing device 200. This configurationallows a user of the clinical testing device 200 to take a proper actionwhen there is an indication of the occurrence of test strip jamming,thereby allowing the actual occurrence of trouble, i.e. test stripjamming to be prevented.

In the above description, every time an abnormality was caused, a newcondition for prediction was added based on a change pattern of statusdata. However, for example, in the case where an abnormality is causedaccidentally under a particular usage condition or the like, a changepattern of status data obtained right before the occurrence of theabnormality may not necessarily provide a reliable indication of theabnormality. The use of a condition for prediction created based on sucha change pattern even may result adversely in decreased accuracy inpredicting an abnormality.

Therefore, in the host computer 100, when a common abnormality is causedin each of a plurality of the clinical testing devices 200, status dataof each of those clinical testing devices 200 is analyzed, and forexample, only if a common change pattern is observed in a predeterminedor higher number of the clinical testing devices 200, a new conditionfor prediction may be created based on the change pattern. Thus, ageneral condition for prediction used to detect an indication of anabnormality can be set, thereby allowing an abnormality to be predictedmore accurately.

In this case, with respect to each of the plurality of the clinicaltesting devices 200, data (manufacture-related data) including amanufacture lot number, a date of manufacture, and a manufacture lotnumber of a component used in each part further may be stored in thedata storing part 103 or a storing part provided for thismanufacture-related data in the host computer 100. Then, in the casewhere common abnormality data is detected from a plurality of theclinical testing devices 200, the host computer 100 determinesmanufacture lot numbers of the clinical testing devices 200, in each ofwhich an abnormality is caused, a manufacture lot number of a componentused in a part with the abnormality and the like based on themanufacture-related data stored in the data storing part 103 or thelike. Moreover, in the case where, for example, a manufacture lot numberof a device, a manufacture lot number of a component with an abnormalityand the like are common to all or a part of the plurality of theclinical testing devices 200 in each of which the abnormality is caused,the clinical testing device 200 assigned the same manufacture lot numberor the clinical testing device 200 using a component assigned the samemanufacture lot number as that assigned to a component with theabnormality is determined among the monitored clinical testing devices200. Thus, with respect to the clinical testing device 200 thusdetermined, a proper action can be taken so that the occurrence oftrouble can be prevented.

The above-mentioned embodiments are not to limit the present inventionthereto and can be modified variously within the scope of the invention.For example, in the above description, during the operation of theclinical testing device 200 in actual use by a user, status data wastransmitted to the host computer 100 as required, and upon theoccurrence of an abnormality, a new condition for prediction wascreated. However, aside from this configuration, a condition forprediction may be creased based on a change pattern of status dataobtained from a manufacturer/dealer of the clinical testing device 200when an abnormality is caused in the clinical testing device 200operated on a trial basis and stored in the condition storing part 104of the host computer 100 so as to be used.

Furthermore, the monitoring device according to the present invention isnot limited to a host computer such as the one mentioned above and canbe realized by using an arbitrary computer such as a personal computer,a workstation or the like. Further, the monitored device is not limitedto a clinical testing device, and an arbitrary device requiring a checkand maintenance such as an automobile or the like can be appliedthereto. Further, household electrical appliances that do notnecessarily require a check and maintenance also may be applied thereto.Moreover, the connection between the monitored device and thecommunication network is not limited to connection by wire, and mobilecommunication, and connection by radio such as Home RF, Bluetooth andthe like also may be used.

In each of the monitoring systems described in the above-mentionedembodiments, status data are collected from a device in actual use by auser, and a condition for prediction is created based on a changepattern of the status data. On the other hand, for example, aconfiguration also is possible in which an endurance test or the like isperformed by a manufacturer of a clinical testing device or the likeusing a device for a test that has been extracted suitably from deviceson a manufacturing line, and a condition for prediction is created basedon status data obtained during this test. Nevertheless, according to themonitoring system of this embodiment, a condition for prediction meetingan actual use environment and usage conditions can be created, and thusan abnormality can be predicted more accurately than in the case ofusing a condition for prediction obtained on a trial basis.

Moreover, this monitoring system allows a plurality of clinical testingdevices and the like to be connected to a monitoring device through acommunication network. As described above, a configuration also ispossible in which a condition for prediction is created by amanufacturer using a device for a test that has been extracted fromdevices on a manufacturing line. However, generally, the number ofdevices that can be used in a test is limited. On the other hand, in themonitoring system according to this embodiment, logically, devices ofall users can be monitored, and a condition for prediction can becreated based on status data obtained from a plurality of devices. Thus,a more general condition for prediction can be created, thereby allowingan abnormality to be predicted even more accurately.

Furthermore, in the monitoring device of this monitoring system, a newcondition for prediction that has been created so as to be suitable isadded in a condition storing part as required, and thus the longer anoperating period of a system, the more effective the conditions forprediction being accumulated can be, thereby allowing an abnormality tobe detected even more accurately. Thus, the following effects can beachieved. That is, the normal operating ratio of a clinical testingdevice or the like further can be improved, and thus increasedsatisfaction of users can be achieved, and an increase in maintenancecost also can be suppressed further.

INDUSTRIAL APPLICABILITY

As described in the foregoing discussion, according to the presentinvention, a state of a monitored device is monitored remotely so thatan indication of an abnormality is detected, and thus a monitoringsystem can be provided in which a maintenance check can be performed atan appropriate time, thereby allowing a monitored device to achieve ahigher normal operating ratio and the suppression of an increase inmaintenance cost.

1. A monitoring device, comprising: a status data receiving part thatreceives status data representing a status of a monitored device fromthe monitored device through a communication network; a conditionstoring part that stores a condition for prediction; a status monitoringpart that compares the status data with the condition for prediction inthe condition storing part so as to predict an abnormality, wherein thecondition for prediction includes a condition for prediction createdbased on a change pattern of the status data that provides an indicationof the abnormality, the status data being obtained before a point intime at which the abnormality is caused in the monitored device; a datastoring part that accumulates the status data received from themonitored device; and an abnormality analyzing part that newly createsthe condition for prediction based on a transition of the status databefore the point in time at which the abnormality is caused using thestatus data accumulated in the data storing part and has the conditionfor prediction stored in the condition storing part, wherein when thestatus data meets either of the condition for prediction newly createdby the abnormality analyzing part or the condition for predictionprestored in the condition storing part, the status monitoring partjudges that there is a high possibility of occurrence of theabnormality.
 2. The monitoring device according to claim 1, wherein thecondition for prediction created is a condition created based ontransitions of the status data with a common change pattern amongtransitions of the status data that are observed in at least twomonitored devices in which a common abnormality is caused.
 3. Themonitoring device according to claim 1, wherein the condition forprediction further includes a condition for prediction created based onlife data of a component of the monitored device.
 4. The monitoringdevice according to claim 1, wherein the status data includes outputs ofvarious types of sensors that are provided in the monitored device, andthe condition for prediction includes a condition for predictioncorresponding respectively to the outputs of the various types ofsensors.
 5. The monitoring device according to claim 1, furthercomprising a communication part that transmits a notification that anabnormality is predicted by the status monitoring part to the monitoreddevice through the communication network.
 6. The monitoring deviceaccording to claim 5, wherein the communication part transmits adirection on how to correct the abnormality.
 7. The monitoring deviceaccording to claim 1, wherein the monitored device comprises a componentthat performs a predetermined operation repeatedly in the case where thepredetermined operation has failed to be completed successfully, and anumber of repetitions of the predetermined operation performed tillsuccessful completion is output as the status data, and a condition forprediction used to predict an abnormality of the component includes thata value of the status data corresponding to the number of repetitionsbecomes higher than values in a predetermined range.
 8. The monitoringdevice according to claim 1, wherein manufacture-related data regardingeach of the monitored devices are stored, upon detection of occurrenceof a common abnormality in a plurality of the monitored devices, themonitoring device refers to the manufacture-related data regarding theplurality of the monitored devices, and in the case where there is apiece of the manufacture-related data common to at least part of theplurality of the monitored devices, the monitoring device determines themonitored devices, each applying to the piece of the manufacture-relateddata, other than the at least part of the plurality of the monitoreddevices.
 9. The monitoring device according to claim 8, wherein themanufacture-related data includes at least one piece of data selectedfrom the group consisting of: a manufacture lot identifier of amonitored device, a date of manufacture of the monitored device, amanufacture lot identifier of a component of the monitored device, and adate of manufacture of the component of the monitored device.
 10. Aprogram recording medium on which a program is recorded that allows acomputer to perform a process characterized by: receiving status datarepresenting a status of a monitored device from the monitored device;comparing the status data with a condition for prediction that wasstored in a condition storing part and includes a condition createdbased on a change pattern of the status data that provides an indicationof an abnormality, the status data being obtained before a point in timeat which the abnormality is caused in the monitored device with thestatus data; accumulating the status data received from the monitoreddevice; newly creating the condition for prediction based on atransition of the status data before the point in time at which theabnormality is caused, using the status data accumulating in the datastoring part, and storing the condition for prediction in the conditionstorage part; and providing to the monitored device a notification thatabnormality is predicted when the status data meets either of thenewly-created condition for prediction or the condition for predictionprestored in the condition storage part.